The following is the research paper discussed in this section: DeepSite: Protein-binding site predictor using 3D-convolutional neural networks, J Jiménez, S Doerr, G Martínez-Rosell, A S Rose, G D Fabritiis (2017), Bioinformatics, 33(19), 3036-3042, doi:10.1093/bioinformatics/btx350.
Drug target discovery is the method of finding a potential site or pocket on a target protein where a small molecule can dock on to. This method has the larger goal of addressing a particular disease that the target protein is related to.
DeepSite is a protein-binding site predictor that uses 3D convolutional neural networks. The novel knowledge-based approach uses state-of-the-art convolutional neural networks. The algorithm learns by examples from 7,622 proteins from the scPDB database of binding sites using both a distance and a volumetric overlap approach.
The machine learning-based method that was developed by the scientists demonstrates superior performance compared to two other competitive algorithmic strategies. Users can submit a protein structure file for pocket detection to their NVIDIA GPU-equipped servers through a WebGL graphical interface to study and find new sites on proteins for potential docking.